1. Using the Stages of Change Model to Select an Optimal Health Marketing Target Paula Diehr, Ph.D. Health Marketing Research Center CDC Center of Excellence Biostatistics and Health Services SPHCM University of Washington

2. Goal Use Stages of Change model to determine the best intervention target to decrease population smoking Use Stages of Change model to determine the best intervention target to decrease population smoking Same target suggested by health marketing principles? Same target suggested by health marketing principles?

3. Outline Stages of Change Stages of Change Data – estimate probability of changing stages Data – estimate probability of changing stages Probabilities  Multi-state life table Probabilities  Multi-state life table Expected number of years spent in Maintenance Expected number of years spent in Maintenance Hypothetical Interventions – alter 1 probability Hypothetical Interventions – alter 1 probability Best intervention – most years in Maintenance Best intervention – most years in Maintenance Compare to Health Marketing recommendation Compare to Health Marketing recommendation Smoking Example Smoking Example

4. Stages of Behavior Change (Prochaska, Transtheoretic Model) Pre-contemplation Pre-contemplation (not even thinking about stopping smoking) (not even thinking about stopping smoking) Contemplation Contemplation Preparation Preparation Action (short-term smoking abstinence) Action (short-term smoking abstinence) Maintenance (long-term smoking abstinence) Maintenance (long-term smoking abstinence)

5. Stages of Change Model ContPrecontPrepMaintAction

6. + Never Smoker ContPrePrepMaintActionNever

7. ContPrePrepMaintActionNever Dead PreNever Prep + Dead

8. Transition Probabilities (2 Yrs) t1/ t2 PreContPrepActMaintNever Pre.63.16.05.10.060 Cont.37.29.12.11.110 Prepar.24.24.26.12.140 Action.08.12.06.14.590 Maint.01.01.01.02.950 Never.001.001.002.004.04.95

9. Transition Probabilities (2 Yrs) t1/ t2 PreContPrepActMaintNever Pre.63.16.05.10.060 Cont.37.29.12.11.110 Prepar.24.24.26.12.140 Action.08.12.06.14.590 Maint.01.01.01.02.950 Never.001.001.002.004.04.95

10. Transition Probabilities (2 Yrs) t1/ t2 PreContPrepActMaintNever Pre.63.16.05.10.060 Cont.37.29.12.11.110 Prepar.24.24.26.12.140 Action.08.12.06.14.590 Maint.01.01.01.02.950 Never.001.001.002.004.04.95

11. Multi-State Life Table (age 40) Life Expectancy=36 yrs Maintenance=26 yrs

12. Public Health Interventions People move among stages with certain probabilities People move among stages with certain probabilities Can improve population health (reduce smoking) by changing the probabilities Can improve population health (reduce smoking) by changing the probabilities Suppose we could change one probability Suppose we could change one probability Which probability should we change? Which probability should we change?

13. ContPrePrepMaintActionNever Dead PreNever Prep Disparities Perspective Prob=0.16 10% Higher

14. ContPrePrepMaintActionNever Dead PreNever Prep Prevention Perspective Prob=0.04 10% Lower

15. Social Marketing Perspective SM uses marketing principles to achieve specific behavioral goals SM uses marketing principles to achieve specific behavioral goals Principle 1 --- Low-hanging fruit Principle 1 --- Low-hanging fruit Target the markets most ready for change Target the markets most ready for change Principle 2 --- Customer relationship management (customer loyalty) Principle 2 --- Customer relationship management (customer loyalty) Cheaper to keep a current customer than to get a new one Cheaper to keep a current customer than to get a new one

16. ContPrePrepMaintActionNever Dead PreNever Prep “Low Hanging Fruit” Prob=0.59 10% Higher

17. ContPrePrepMaintActionNever Dead PreNever Prep “Customer Relationship Mgmt” Prob=0.02 10% Lower

18. Which Intervention is Best? Improve each transition probability by 10% Improve each transition probability by 10% Calculate new multi-state life table Calculate new multi-state life table Calculate expected years spent in Maintenance Calculate expected years spent in Maintenance Compare interventions Compare interventions Choose intervention that gives the most years spent in Maintenance Choose intervention that gives the most years spent in Maintenance

19. Transitions and Interventions PreContPrepActMaintNever Pre.63.16 (1).05.10.060 Cont.37 (2).29.12 (3).11.110 Prep.24.24 (4).26.12 (5).140 Act.08.12.06 (6).14.59 (7) 0 Maint.01.01.01.02 (8).950 Never.001.001.002.004.04 (9).95

20. Hypothetical Interventions # Transition probability to be improved 0 Status Quo 1 Precontemplation  Contemplation (Disparities) 2 Precontemplation  Contemplation 3 Contemplation  Preparation 4 Contemplation  Preparation 5 Preparation  Action 6 Preparation  Action 7 Action  Maintenance (Low Hanging Fruit) 8 Smoker  Maintenance (Customer Relationship ) 9 Ever Smokers  Never Smoker (Prevention)

21. RESULTS Dataset 123 Initial Distribution: All Precontemplation 777 All Contemplation 777 All Preparation 77 All Action 777 All Maintenance 788 Baseline (no Never) 777 All Never Smokers 9 Baseline + Never 9

22. Dataset123 Initial Distribution: All Precontemplation 777 All Contemplation 777 All Preparation 77 All Action 777 All Maintenance 788 Baseline (no Never) 777 All Never Smokers 9 Baseline + Never 9

23. Summary of Results Intervention 7 (low hanging fruit) is usually the best if population of interest is ever smokers Intervention 7 (low hanging fruit) is usually the best if population of interest is ever smokers Intervention 8 (customer relationship) is usually best if all in Maintenance at age 40 Intervention 8 (customer relationship) is usually best if all in Maintenance at age 40 Intervention 9 (prevention) if population of interest includes many never smokers Intervention 9 (prevention) if population of interest includes many never smokers Social marketing principles worked! Social marketing principles worked!

24. What Stage to Target? Current Smokers (Precont, Contemp, Prep) Current Smokers (Precont, Contemp, Prep) Smoking Cessation (#1-5) Smoking Cessation (#1-5) Never best Never best Former Smokers (Action, Maintenance) Former Smokers (Action, Maintenance) Relapse Prevention (#6, 7, 8) Relapse Prevention (#6, 7, 8) Best if population is former or current smokers Best if population is former or current smokers Never Smokers Never Smokers Primary prevention (#9) Primary prevention (#9) Best if population has many never smokers Best if population has many never smokers

25. Why not current smokers? Life Table Example Life Table Example Precontemplators do move on to higher stages under the status quo Precontemplators do move on to higher stages under the status quo Quitting smoking is easy. I’ve done it a thousand times. Quitting smoking is easy. I’ve done it a thousand times. Interventions to help quitters stay quit had more long-term effectiveness Interventions to help quitters stay quit had more long-term effectiveness

26. Limitations Data Data 3 different datasets have complementary weaknesses 3 different datasets have complementary weaknesses Data optimistically biased? (sensitivity analyses) Data optimistically biased? (sensitivity analyses) Gender Gender Started at age 40 – younger of interest Started at age 40 – younger of interest Real interventions Real interventions improve >1 transition probability improve >1 transition probability might change other probabilities by changing norms might change other probabilities by changing norms Cost effectiveness not discussed Cost effectiveness not discussed

27. Conclusion Support for smoking prevention and relapse prevention rather than for smoking cessation Support for smoking prevention and relapse prevention rather than for smoking cessation Health Marketing principles Health Marketing principles Heartless? Heartless? Agreed with “optimum” intervention from Stages of Change Model Agreed with “optimum” intervention from Stages of Change Model Even for the worst-off smokers (Precontemplators) Even for the worst-off smokers (Precontemplators) Support for the use of Health Marketing Principles to target smoking interventions Support for the use of Health Marketing Principles to target smoking interventions

28. Future Are these findings true for other behaviors? Are these findings true for other behaviors? Younger age? Sex? Younger age? Sex? Probably Probably More and better smoking data More and better smoking data Data on stages of change for other behaviors Data on stages of change for other behaviors

29. Technical Report http://faculty.washington.edu/pdiehr/stages.doc pdiehr@u.washington.edu

30. The End

31. 3 datasets CHPGP CHPGP N~10,000 2-year transitions N~10,000 2-year transitions age-specific estimates of change age-specific estimates of change all stages all stages Poor operationalization of Precontemplation and Contemplation Poor operationalization of Precontemplation and Contemplation Martin Martin N~500 6-month transitions N~500 6-month transitions No “Preparation” or “Never” No “Preparation” or “Never” Pizacani Pizacani N~500 2-year transitions N~500 2-year transitions No follow-up data for Action, Maintenance, Never No follow-up data for Action, Maintenance, Never

32. Sensitivity Analyses Rate of smoking initiation lower Rate of smoking initiation lower Rate of relapse from Maintenance higher Rate of relapse from Maintenance higher Rate of remaining in Precontemplation higher Rate of remaining in Precontemplation higher.63 .85.63 .85 Different objectives Different objectives Survival, partial credit for lower stages Survival, partial credit for lower stages Different time horizons – 4 yrs, 10 yrs Different time horizons – 4 yrs, 10 yrs

33. Three Datasets Wagner E, et al: The evaluation of the Kaiser Family Foundation's community health promotion grants program (CHPGP ): Overall design. J Clin Epidemiol 1991; 44:685-699. [N = 10,000, all stages] Wagner E, et al: The evaluation of the Kaiser Family Foundation's community health promotion grants program (CHPGP ): Overall design. J Clin Epidemiol 1991; 44:685-699. [N = 10,000, all stages] Martin RA, et al: Latent transition analysis to the stages of change for smoking cessation, Addict. Behav 1996; 21:67–80. [N = 500, missing stages] Martin RA, et al: Latent transition analysis to the stages of change for smoking cessation, Addict. Behav 1996; 21:67–80. [N = 500, missing stages] Pizacani B, et al: A prospective study of household smoking bans and subsequent cessation related behaviour: the role of stage of change. Tob Control. 2004; 13:23-28. [n=500, missing stages] Pizacani B, et al: A prospective study of household smoking bans and subsequent cessation related behaviour: the role of stage of change. Tob Control. 2004; 13:23-28. [n=500, missing stages]

34. Table 1, Stage Definitions

35. 3 datasets (cont.)